AI-Powered IT Service Management for Predictive Maintenance in Manufacturing: Leveraging Machine Learning to Optimize Service Request Management and Minimize Downtime
Keywords:
AI-powered ITSM, machine learning, predictive maintenanceAbstract
The AI/ML enhanced operations, downtime, and service management in manufacturing and other sectors. ITSM systems call for predictive maintenance powered by artificial intelligence to automate service request management and maintain critical industrial equipment. Although reactive service request management results in generalocation and downtime, many operational settings find value in classic ITSM systems. This reactive strategy may have major financial and operational consequences especially in industry, where even little equipment failures may entail production delays and costly repairs. Predictive ML/AI support proactive maintenance. Machine learning approaches using real-time and historical data to anticipate and fix equipment issues may improve service management.
ITSM systems could enhance industrial predictive maintenance by means of artificial intelligence/machine learning. Massive production data lets machine learning methods identify trends, patterns, and issues not feasible for traditional monitoring systems. These methods find, fix, and ask for repairs using predictive analytics, therefore averting equipment failure. Database driven maintenance optimizes resources and reduces equipment downtime.
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